We provide a joint account of the unemployment and labor force participation patterns of older male workers during the past half-century, and of the role of institutions that have shaped their employment experience. To do so, we build an equilibrium model with labor market frictions,...

This paper studies the secular behavior of worker reallocation across occupations in the US labor market. In the empirical analysis, we use 45 years of microdata to construct consistent time-series and document that the fraction of employment reallocated annually across occupations is remarkably...

Much of the literature on interest rate pass through assumes banks set retail rates in relation to contemporary market rates. We argue that future rates also matter, and if forecasts of future rates are included, the empirical specifications of many previous studies are misspecified. Including...

This paper analyses the use of factor analysis for instrumental variable estimation when the number of instruments tends to infinity. In particular, we focus on situations where many weak instruments exist and/or the factor structure is weak. Theoretical results, simulation experiments and...

As a generalization of the factor-augmented VAR (FAVAR) and of the Error Correction Model (ECM), Banerjee and Marcellino (2009) introduced the Factor-augmented Error Correction Model (FECM). The FECM combines error-correction, cointegration and dynamic factor models, and has several conceptual...

The standard approach to modelling coffee prices ignores the impact that changes in government policies and market structures has on coffee prices. These changes have led to large structural breaks in coffee prices implying the standard estimates are biased. This paper models coffee princes in...

This paper brings together several important strands of the econometrics literature: error-correction, cointegration and dynamic factor models. It introduces the Factor-augmented Error Correction Model (FECM), where the factors estimated from a large set of variables in levels are jointly...

As a generalization of the factor-augmented VAR (FAVAR) and of the Error Correction Model (ECM), Banerjee and Marcellino (2009) introduced the Factor- augmented Error Correction Model (FECM). The FECM combines error-correction, cointegration and dynamic factor models, and has several conceptual...

As a generalization of the factor-augmented VAR (FAVAR) and of the Error Correction Model (ECM), Banerjee and Marcellino (2009) introduced the Factor- augmented Error Correction Model (FECM). The FECM combines error-correction, cointegration and dynamic factor models, and has several conceptual...

The Factor-augmented Error Correction Model (FECM) generalizes the factor-augmented VAR (FAVAR) and the Error Correction Model (ECM), combining error-correction, cointegration and dynamic factor models. It uses a larger set of variables compared to the ECM and incorporates the long-run...